In silico analysis of metabolic effects of bipolar disorder on prefrontal cortex identified altered GABA, glutamate-glutamine cycle, energy metabolism and amino acid synthesis pathways.

IF 1.5 4区 生物学 Q4 CELL BIOLOGY Integrative Biology Pub Date : 2022-10-14 DOI:10.1093/intbio/zyac012
Hamza Umut Karakurt, Pınar Pir
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Abstract

Bipolar disorder (BP) is a lifelong psychiatric condition, which often disrupts the daily life of the patients. It is characterized by unstable and periodic mood changes, which cause patients to display unusual shifts in mood, energy, activity levels, concentration and the ability to carry out day-to-day tasks. BP is a major psychiatric condition, and it is still undertreated. The causes and neural mechanisms of bipolar disorder are unclear, and diagnosis is still mostly based on psychiatric examination, furthermore the unstable character of the disorder makes diagnosis challenging. Identification of the molecular mechanisms underlying the disease may improve the diagnosis and treatment rates. Single nucleotide polymorphisms (SNP) and transcriptome profiles of patients were studied along with signalling pathways that are thought to be associated with bipolar disorder. Here, we present a computational approach that uses publicly available transcriptome data from bipolar disorder patients and healthy controls. Along with statistical analyses, data are integrated with a genome-scale metabolic model and protein-protein interaction network. Healthy individuals and bipolar disorder patients are compared based on their metabolic profiles. We hypothesize that energy metabolism alterations in bipolar disorder relate to perturbations in amino-acid metabolism and neuron-astrocyte exchange reactions. Due to changes in amino acid metabolism, neurotransmitters and their secretion from neurons and metabolic exchange pathways between neurons and astrocytes such as the glutamine-glutamate cycle are also altered. Changes in negatively charged (-1) KIV and KMV molecules are also observed, and it indicates that charge balance in the brain is highly altered in bipolar disorder. Due to this fact, we also hypothesize that positively charged lithium ions may stabilize the disturbed charge balance in neurons in addition to its effects on neurotransmission. To the best of our knowledge, our approach is unique as it is the first study using genome-scale metabolic models in neuropsychiatric research.

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通过对双相情感障碍对前额叶皮层代谢影响的硅学分析,确定了 GABA、谷氨酸-谷氨酰胺循环、能量代谢和氨基酸合成途径的改变。
躁郁症(Bipolar disorder,简称 BP)是一种终身性精神疾病,通常会扰乱患者的日常生活。躁郁症的特点是不稳定和周期性的情绪变化,导致患者在情绪、精力、活动水平、注意力和执行日常任务的能力方面出现不寻常的变化。双相情感障碍是一种主要的精神疾病,但目前仍未得到充分治疗。躁狂症的病因和神经机制尚不清楚,诊断仍主要依靠精神检查,此外,该疾病的不稳定性也给诊断带来了挑战。鉴定该疾病的分子机制可以提高诊断率和治疗率。我们研究了患者的单核苷酸多态性(SNP)和转录组图谱,以及被认为与躁狂症相关的信号通路。在这里,我们提出了一种计算方法,该方法使用了双相情感障碍患者和健康对照组的公开转录组数据。在进行统计分析的同时,我们还将数据与基因组规模的代谢模型和蛋白质-蛋白质相互作用网络进行了整合。健康人和躁郁症患者根据其代谢特征进行比较。我们假设,躁郁症患者的能量代谢改变与氨基酸代谢和神经元-胃囊交换反应的紊乱有关。由于氨基酸代谢的变化,神经递质及其从神经元的分泌以及神经元和星形胶质细胞之间的代谢交换途径(如谷氨酰胺-谷氨酸循环)也发生了改变。我们还观察到带负电荷(-1)的 KIV 和 KMV 分子发生了变化,这表明躁郁症患者大脑中的电荷平衡发生了很大变化。基于这一事实,我们还假设,带正电荷的锂离子除了对神经传递产生影响外,还可能稳定神经元中紊乱的电荷平衡。据我们所知,我们的研究方法是独一无二的,因为这是首次在神经精神疾病研究中使用基因组规模的代谢模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Integrative Biology
Integrative Biology 生物-细胞生物学
CiteScore
4.90
自引率
0.00%
发文量
15
审稿时长
1 months
期刊介绍: Integrative Biology publishes original biological research based on innovative experimental and theoretical methodologies that answer biological questions. The journal is multi- and inter-disciplinary, calling upon expertise and technologies from the physical sciences, engineering, computation, imaging, and mathematics to address critical questions in biological systems. Research using experimental or computational quantitative technologies to characterise biological systems at the molecular, cellular, tissue and population levels is welcomed. Of particular interest are submissions contributing to quantitative understanding of how component properties at one level in the dimensional scale (nano to micro) determine system behaviour at a higher level of complexity. Studies of synthetic systems, whether used to elucidate fundamental principles of biological function or as the basis for novel applications are also of interest.
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